The Fraud-Protection Paradox in Consumer Payments

Taif Khalid Shakir1 Ahmed N. Al Masri2,*

1 Ascencia Business School, College de Paris, France

2 Department of Studies, Research and Development, Ministry of Energy and Infrastructure, Abu Dhabi 11191, United Arab Emirates

Received: January 03, 2024 Revised: March 01, 2024 Accepted: June 05, 2024 ⋆ Corresponding author

ABSTRACT

Consumer-payment risk is hard to measure because instruments that have the highest incidence of reported fraud are

often still in high usage and trusted. The key debate is when to break down the line between weak security and a

protection ecosystem that will minimise the impact consumers suffer following an incident, through monitoring,

liability allocation, dispute handling and recovery. This paper constructs a framework for risk alignment between

instrument-level fraud incidence, perceived security, and realized payment use, and breaks down the difference

between persistent instrument-level differences and short-run changes within instruments. Official U.S. estimates

for cash, checks, debit cards, and credit cards are arranged in a balanced panel for the years 2015-2020 and an

extended descriptive sample for 2022. Combined results of pooled regression, two-way fixed effects, first differences,

and leave-one-year-out ridge validation to ascertain if fraud exposure can be predicted after accounting for stable

instrument characteristics and common annual shocks. Regulators and payment providers need to address this

measurement challenge since a narrow focus on incident counts can divert investment focus from detection, liability

limits, recovery, and reimbursement capabilities that build consumer confidence and payment-system robustness.

Credit-card payment share rose from 18.3% in 2015 to 31.3% in 2022 while 10.3% of adopters reported loss, theft,

or fraud in 2022; the pooled fraud coefficient of 3.86 (p < .001) fell to 2.20 (p = .185) under instrument and

year fixed effects, and lagged fraud did not predict annual share change (−0.27, p = .401). The validation using

leave-one-year-out results in an R2 = .873 and MAE of 2.90 percentage points, whereas the instrument-history

validation produces an MAE of 2.71.

Keywords: Payment fraud Consumer payments FinTech Perceived security Payment choice Digital financial

services

1. INTRODUCTION

Payment has evolved in both the instruments that consumers

use and the infrastructure that enables transactions to be authorized,

monitored and settled. The greater the surface area

of a transaction, the more opportunities for loss, theft, and

fraud. Cards, mobile interfaces, tokenized credentials and

platform-based services increase transaction friction, but they

also increase the surface area through which it can occur. A

rule of thumb in the standard behavioral expectation is that an

instrument that seems insecure will lose users and transaction

share. Real payment behavior is not as straightforward. Despite

reports of credit and debit card fraud, they continue to

be the leading payment methods, and a number of low-fraud

instruments are on the downside.

For financial tech, this discrepancy is significant since security

is not perceived as a one-time possibility. Consumers can

differentiate between the probability of an event happening

and the impact that it will have on them. When the inci-